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102 lines
3.4 KiB
102 lines
3.4 KiB
#!/usr/bin/env python
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# Copyright (c) Facebook, Inc. and its affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the license found in
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# https://github.com/pytorch/fairseq/blob/master/LICENSE
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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from __future__ import unicode_literals
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import argparse
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import contextlib
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import sys
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import sentencepiece as spm
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def main():
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parser = argparse.ArgumentParser()
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parser.add_argument("--model", required=True,
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help="sentencepiece model to use for encoding")
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parser.add_argument("--inputs", nargs="+", default=['-'],
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help="input files to filter/encode")
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parser.add_argument("--outputs", nargs="+", default=['-'],
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help="path to save encoded outputs")
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parser.add_argument("--output_format", choices=["piece", "id"], default="piece")
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parser.add_argument("--min-len", type=int, metavar="N",
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help="filter sentence pairs with fewer than N tokens")
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parser.add_argument("--max-len", type=int, metavar="N",
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help="filter sentence pairs with more than N tokens")
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args = parser.parse_args()
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assert len(args.inputs) == len(args.outputs), \
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"number of input and output paths should match"
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sp = spm.SentencePieceProcessor()
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sp.Load(args.model)
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if args.output_format == "piece":
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def encode(l):
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return sp.EncodeAsPieces(l)
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elif args.output_format == "id":
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def encode(l):
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return list(map(str, sp.EncodeAsIds(l)))
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else:
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raise NotImplementedError
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if args.min_len is not None or args.max_len is not None:
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def valid(line):
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return (
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(args.min_len is None or len(line) >= args.min_len) and
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(args.max_len is None or len(line) <= args.max_len)
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)
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else:
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def valid(lines):
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return True
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with contextlib.ExitStack() as stack:
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inputs = [
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stack.enter_context(open(input, "r", encoding="utf-8"))
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if input != "-" else sys.stdin
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for input in args.inputs
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]
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outputs = [
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stack.enter_context(open(output, "w", encoding="utf-8"))
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if output != "-" else sys.stdout
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for output in args.outputs
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]
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stats = {
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"num_empty": 0,
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"num_filtered": 0,
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}
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def encode_line(line):
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line = line.strip()
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if len(line) > 0:
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line = encode(line)
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if valid(line):
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return line
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else:
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stats["num_filtered"] += 1
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else:
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stats["num_empty"] += 1
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return None
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for i, lines in enumerate(zip(*inputs), start=1):
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enc_lines = list(map(encode_line, lines))
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if not any(enc_line is None for enc_line in enc_lines):
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for enc_line, output_h in zip(enc_lines, outputs):
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print(" ".join(enc_line), file=output_h)
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if i % 10000 == 0:
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print("processed {} lines".format(i), file=sys.stderr)
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print("skipped {} empty lines".format(stats["num_empty"]), file=sys.stderr)
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print("filtered {} lines".format(stats["num_filtered"]), file=sys.stderr)
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if __name__ == "__main__":
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main()
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